code: def test_ner_chinese():
      download_ecommerce()
      train_df, dev_df = get_data()
      predictor = MultiModalPredictor(
          problem_type="ner",
          label="entity_annotations",
      )
      predictor.fit(
          train_data=train_df,
          tuning_data=dev_df,
          hyperparameters={
              "model.ner_text.checkpoint_name": "hfl/chinese-lert-small",
              "optimization.top_k": 1,
              "env.num_gpus": -1,
              "optimization.max_epochs": 1,
          },
      )
      predictor.evaluate(dev_df)
      predictor.predict(dev_df.head(2))
  
file_path: autogluon/multimodal/tests/unittests/others_2/test_ner_chinese.py
imports: import json
  import os
  import pandas
  from autogluon.multimodal import MultiModalPredictor
  from autogluon.multimodal.utils import download
  from ..utils.utils import get_home_dir
label_desc: Use image node_id 5 for calling a global function with example usage: test_ner_chinese() without return types